About the Journal
Aims & Scope
Transactions on Intelligent Robotics and Autonomous Systems (TIRAS) is a peer-reviewed, open access journal published by Kaggleyes Academy. The journal covers intelligent robotics and autonomous systems, including robot navigation, locomotion, control, perception, planning, and learning for legged, wheeled, and heterogeneous robot teams. TIRAS publishes original research, methods, and systems papers, with a strong emphasis on reproducible experiments and deployed results.
Journal Information
| Abbreviated title | TIRAS |
|---|---|
| ISSN | 3083-4471 (online) |
| Publisher | Kaggleyes Academy |
| First issue | Vol. 1, No. 1 (July 2026) |
| Frequency | Monthly |
| Peer review | Double-blind review, two or more reviewers |
| Open access | All articles are immediately open access under CC BY 4.0 |
| Article charges | No submission, review, or publication charges |
| Identifiers | Each article receives a permanent KAGG article ID and a DOI (10.5803/kagg.YYMM.NNNNN) |
| Indexing | Articles are indexed by Google Scholar |
Peer Review
Manuscripts are handled by the editorial office and reviewed by at least two anonymous reviewers. Authors are asked to prepare anonymized submissions; the published version may contain a camera-ready manuscript with author information. Reviewers assess significance, soundness, clarity, and reproducibility. After acceptance, articles appear in the next monthly issue.
Open Access Policy
This journal provides immediate open access to all articles under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. Authors retain copyright; readers may read, download, copy, distribute, print, search, or link to the full text of articles without permission, provided the original authors and source are credited.
Editorial Office
Kaggleyes Academy
Editorial office: editorial@kaggleyes.top
Manuscript inquiries are answered by the editorial office on behalf of the
TIRAS editors.
TIRAS article IDs of the form KAGG:YYMM.NNNNN are permanent local identifiers issued by Kaggleyes Academy. They map one-to-one to DOI names of the form 10.5803/kagg.YYMM.NNNNN.